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Evaluation of postoperative pain and antibacterial efficacy of nanochitosan and sodium hypochlorite in endodontics: A randomized controlled trial. [PDF]
J Conserv Dent EndodPrasad LK, Nikhat S.
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Forecasting Univariate Root-Mean-Square Vibration Sequences: A Benchmark of Statistical, Deep Learning, and Foundation Models on Two Rotating-Machinery Datasets. [PDF]
Sensors (Basel)Le TT, Shin D, Lee S, Kim H.
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Prevalence and morphology of lingual canals in mandibular incisors: a cone-beam computed tomography-based cross-sectional study. [PDF]
PeerJRamalho CLG +5 more
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Wiley Interdisciplinary Reviews: Computational Statistics, 2017
Unit roots are nonstationary autoregressive (AR) or autoregressive moving average (ARMA) time series processes which may include an intercept and/or a trend. These processes are used often in economics and finance, but can also be found in other scientific fields. Unit root tests address the null hypothesis of a unit root, and an alternative hypothesis
exaly +3 more sources
Unit roots are nonstationary autoregressive (AR) or autoregressive moving average (ARMA) time series processes which may include an intercept and/or a trend. These processes are used often in economics and finance, but can also be found in other scientific fields. Unit root tests address the null hypothesis of a unit root, and an alternative hypothesis
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Econometrica, 1981
Summary: [For part I see ibid. 49, 753-779 (1981; Zbl 0468.62021).] This paper investigates the exact sampling distribution of the least squares estimator of \(\beta\) in the model \(y_ t=\mu +\beta y_{t- 1}+u_ t\) where the \(u_ t\) are independently \(N(0,\sigma^ 2)\). The distribution is calculated for the case where \(y_ 0\) is a known constant and
Evans, G. B. A., Savin, N. E.
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Summary: [For part I see ibid. 49, 753-779 (1981; Zbl 0468.62021).] This paper investigates the exact sampling distribution of the least squares estimator of \(\beta\) in the model \(y_ t=\mu +\beta y_{t- 1}+u_ t\) where the \(u_ t\) are independently \(N(0,\sigma^ 2)\). The distribution is calculated for the case where \(y_ 0\) is a known constant and
Evans, G. B. A., Savin, N. E.
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Allgemeines Statistisches Archiv, 2006 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wolters, Jürgen, Hassler, Uwe
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Applied Economics, 1997
Unit root tests have been known for a long time to suffer from a variety of problems. Considering that simulation methods are obvious candidates for solving some of these problems, the aim of this paper is to assess the performance of bootstrap tests of the unit root hypothesis of the Dickey–Fuller type.
DE ANGELIS D +2 more
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Unit root tests have been known for a long time to suffer from a variety of problems. Considering that simulation methods are obvious candidates for solving some of these problems, the aim of this paper is to assess the performance of bootstrap tests of the unit root hypothesis of the Dickey–Fuller type.
DE ANGELIS D +2 more
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Testing for Unit Roots in Market Shares*
Marketing Letters, 2001A unique characteristic of marketing data sets is the logical consistency requirement in market share models that market shares are bounded by 0 and 1, and they sum to unity. To take account of this logical consistency requirement, we propose to test for unit roots in individual market share series within the context of a market share attraction (MCI ...
Franses, P.H.B.F. +2 more
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2003
Many economic and financial time series exhibit trending behavior or non-stationarity in the mean. Leading examples are asset prices, exchange rates and the levels of macroeconomic aggregates like real GDP. An important econometric task is determining the most appropriate form of the trend in the data.
Eric Zivot, Jiahui Wang
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Many economic and financial time series exhibit trending behavior or non-stationarity in the mean. Leading examples are asset prices, exchange rates and the levels of macroeconomic aggregates like real GDP. An important econometric task is determining the most appropriate form of the trend in the data.
Eric Zivot, Jiahui Wang
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1993
AbstractMethods of testing for a unit root in an observed series are described in this chapter. Both parametric regression tests and non‐parametric adjustments to these test statistics are considered, and tables of critical values for commonly used tests are given.
Anindya Banerjee +3 more
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AbstractMethods of testing for a unit root in an observed series are described in this chapter. Both parametric regression tests and non‐parametric adjustments to these test statistics are considered, and tables of critical values for commonly used tests are given.
Anindya Banerjee +3 more
openaire +1 more source